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Published on: February 14, 2019
Probabilistic Linkage Creates a Novel Database to Study Bronchiolitis Care in the PICU
Brian F Flaherty1, Mckenna Smith1, Adam Dziorny2
1Divisions of Critical Care.
Insights
Probabilistic linkage accurately combines pediatric critical care databases (PHIS and VPS) for research without patient identifiers. This enables comparative effectiveness research (CER) for bronchiolitis and other PICU conditions.
Area of Science:
- Pediatric critical care medicine
- Health informatics
- Data linkage methodologies
Background:
- Comprehensive databases are crucial for comparative effectiveness research (CER) in pediatric intensive care units (PICUs).
- Existing Pediatric Hospital Information System (PHIS) and Virtual Pediatric Systems (VPS) databases hold valuable data but cannot be linked due to patient identifier restrictions.
- A method is needed to link these datasets for robust CER.
Purpose of the Study:
- To demonstrate that probabilistic linkage can accurately merge PHIS and VPS data without patient identifiers.
- To create a combined database for CER in the PICU, focusing initially on bronchiolitis patients.
Main Methods:
- Probabilistic linkage was employed to connect PHIS and VPS records for patients admitted between July 1, 2017, and June 30, 2019.
- Key metrics included the percentage of matched records, false-positive match rates, and demographic comparisons between linked and unlinked subjects.
Main Results:
- A high linkage rate of 91% (839 of 920 records) was achieved with a low false-positive rate of 0.5% (4 matches).
- No significant differences were observed in age, comorbidities, illness severity, intubation rates, or PICU length of stay between linked and unlinked patients.
Conclusions:
- Probabilistic linkage successfully created an accurate and representative combined database from PHIS and VPS for patients with bronchiolitis.
- This scalable methodology can be applied across 38 contributing hospitals to build a national CER database for various PICU conditions.
Objectives:
Lack of a comprehensive database containing diagnosis, patient and clinical characteristics, diagnostics, treatments, and outcomes limits needed comparative effectiveness research (CER) to improve care in the PICU. Combined, the Pediatric Hospital Information System (PHIS) and Virtual Pediatric Systems (VPS) databases contain the needed data for CER, but limits on the use of patient identifiers have thus far prevented linkage of these databases with traditional linkage methods. Focusing on the subgroup of patients with bronchiolitis, we aim to show that probabilistic linkage methods accurately link data from PHIS and VPS without the need for patient identifiers to create the database needed for CER.
Methods:
We used probabilistic linkage to link PHIS and VPS records for patients admitted to a tertiary children's hospital between July 1, 2017 to June 30, 2019. We calculated the percentage of matched records, rate of false-positive matches, and compared demographics between matched and unmatched subjects with bronchiolitis.
Results:
We linked 839 of 920 (91%) records with 4 (0.5%) false-positive matches. We found no differences in age (P = .76), presence of comorbidities (P = .16), admission illness severity (P = .44), intubation rate (P = .41), or PICU stay length (P = .36) between linked and unlinked subjects.
Conclusions:
Probabilistic linkage creates an accurate and representative combined VPS-PHIS database of patients with bronchiolitis. Our methods are scalable to join data from the 38 hospitals that jointly contribute to PHIS and VPS, creating a national database of diagnostics, treatment, outcome, and patient and clinical data to enable CER for bronchiolitis and other conditions cared for in the PICU.
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